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Sanja Vlaović Begović, Mirela Momčilović and Stevan Tomašević

References Altman, E.I. (1968) “Financial Ratios. Discriminant Analysis and the Prediction of Corporate Bankruptcy,” Journal of Finance, 23(4): 589-609. Altman, E.I. (1983) Corporate Financial Distress, New York, Wiley InterScience. Altman, E.I., Hartzell, J. and Peck, M. (1995) Emerging Markets Corporate Bonds: A Scoring System, Salomon Brothers Inc. New York. Altman, E.I. and Hotchkiss, E. (2006) Corporate Financial Distress & Bankruptcy, 3 rd edition, Hoboken, NJ, J. Wiley & Sons. Altman, E.I., Danovi, A. and Falini, A

Open access

Piotr Korneta

1 Introduction Strategies of many contemporary companies are almost entirely focused on consumers. These companies, with the use of, inter alia, surveys or focus groups, constantly put their consumers under a microscope, aiming to understand their behavior. This is, however, not a straightforward task. Typically, companies tend to look at satisfaction measures, market shares, or sales figures. According to research undertaken by Bain Company, there exists a certain body of consumers, who, despite providing scores indicating “satisfied” in surveys, soon move

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Nicoleta Valentina Florea, Dorina Antoneta Tănăsescu and Anişoara Duică

Abstract

We are in the fifth era of marketing development, that of relationship marketing, where the environment is influenced by globalization, informatization, market liberalization, and the overcapacity of production, and the focus will be not on increasing the volume of production, but on obtaining profit using relationship with profitable customers. Customer-centricity, customization, one-to-one relationship and measuring the value of each customer is an advantage in the fearless market. Organizations if they knew what customers wants would offering only those products or services they want, but to help them to know the customers’ needs better, they use models, new methods and calculation of performance indicators. One of the models which help organizations to determine the customer value and centricity is Net Promoter Score (NPS), its formula being developed by Reichheld F. in 2006. Our research is made on 10 organizations and on 150 respondents and is consisting in using NPS in order to observe customers’ perception of the analysed brands, to measure how well the brand is having satisfayed and loyal customers, and the desire for recommendation of the analysed brand. Our article is using simulation, modeling and IT programs to observe possible relationships and future trends.

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Milka Elena Escalera Chávez and Cristóbal Hernández

References Altman, E. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23: 589-609. DOI: 10.1111/j.1540-6261.1968.tb00843.x. Altman, E. (2013). Predicting financial distress of companies: Revisiting the Z score and zeta models.in Edward Elgar Publishing (eds) Handbook of Research Methods and Applications in Empirical Finance, 428-455.DOI:10.4337/9780857936097.00027 Argenti, J. (1976). Corporate planning and Corporate Collapse. Long Range Planning

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Samuel Ampaw, Edward Nketiah-Amponsah and Bernardin Senadza

-40. Barrett, C., Reardon, T., & Webb, P. (2001). Nonfarm income divesification and household livelihood strategies in rural Africa: Concepts, dynamics and policy implication. Food Policy, 26(4), 315-331. Becker, S. O., & Caliendo, M. (2007). Sensitivity analysis for average treatment effects. The Stata Journal, 7(1), 71-83. Becker, S., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2(4), 358-377. Bezu, S., Barrett, C., & Holden, S. (2012). Does nonfarm economy offer

Open access

Laura Rotar

Economics , 15, (3), pp. 507-528. Becker, S. O., Ichino, A. (2002), "Estimation of Average Treatment Effects Based on Propensity Scores." The Stata Journal , 2, (4), pp. 358-377. Briggs, D. C. (2004), "Causal Inference and the Heckman Model." Journal of Education and Behavioral Statistics , 29, pp. 397-420. Caliendo, M., Hujer, R. (2006), "The Microeconometric Estimation of Treatment Effects. An Overview." Allgemeines Statistisches Archiv , 90, pp. 197-212. Cameron

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Eric Anane and Jephtar Adu-Mensah

References Allen, J., Gregory, A., Mikami, A., Lun, J., Hamre, B., & Pianta, R. (2013). Observations of effective teacher–student interactions in secondary school classrooms: Predicting student achievement with the classroom assessment scoring system - secondary. School Psychology Review , 42 (1), 76. Anane, E. (2011). Predictive validity of continuous assessment scores of students’ performance in end-of-semester examinations in colleges of education in Ghana. Journal of Business and Educational Policies, 7 (1), 95-104. Black, P., Harrison, C

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Darie Moldovan and Mircea Moca

References [1] Tobin, J: A General Equilibrium Approach To Monetary Theory. Journal of Money, Credit and Banking (1) pp.15–29 (1969) [2] Altman, E. I., Saunders, A.: Credit risk measurement: Developments over the last 20 years. Journal of banking & finance, 21(11), pp. 1721-1742 (1997). [3] Weimin Chen, Guocheng Xiang, Youjin Liu, Kexi Wang, Credit risk Evaluation by hybrid data mining technique, Systems Engineering Procedia, 3 (2012) [4] Kambal, E.; Osman, I.; Taha, M.; Mohammed, N.; Mohammed, S. Credit scoring using data mining

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Shoaib Abdul Basit, Thomas Kuhn and Mumtaz Ahmed

+ D de las empresas: un análisis empírico”, Herri ekonomiaz, No. 11, pp. 47-66. 13. Cainelli, G., Evangelista, R., Savona, M. (2004), „The impact of innovation on economic performance in services”, The Service Industries Journal, Vol. 24, No. 1, pp. 116-130. 14. Caliendo, M., Kopeinig, S. (2008), “Some Practical Guidance for the Implementation of Propensity Score Matching”, Journal of Economic Surveys, Vol. 22, No. 1, pp. 31-72. 15. Carboni, O. A. (2017), “The effect of public support on investment and R&D: An empirical evaluation on European

Open access

Rabeb Kammoun

Abstract

Maritime transportation for Tunisia plays an important role in trade exchange with other countries. Therefore, the objective of this paper is to measure the efficiency scores of 7 seaports in Tunisia by applying the Stochastic Frontier Analysis (SFA) with Cobb-Douglas production function and Data envelopment analysis (DEA) with CCR and BCC models. The annual data collected cover the 2007-2017 period for each port. Thus, the sample size for the analysis comprises a total of 77 observations. The empirical result shows that the total average scores of operating efficiency scores were DEA-BCC (0.746) >SFACD (0.536)>DEA-CCR (0.334) from 2007 to 2017. Given these results, the port of Gabes can be considered as the best efficient port in the 3 models (DEA-BCC, DEA-CCR and SFA-CD).